MétaCan
Menu
Back to cohort
Record W2327793129 · doi:10.5692/clinicalneurol.49.838

Pre-symptomatic detection of Alzheimer's disease and mild cognitive impairment

2009· review· en· W2327793129 on OpenAlexaff
Hiroyuki Arai

Bibliographic record

VenueRinsho Shinkeigaku · 2009
Typereview
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsNeuroimagingBiomarkerCognitive impairmentDiseasePositron emission tomographyMedicineCognitive declineDementiaCognitionAlzheimer's diseaseNeurosciencePsychologyInternal medicinePsychiatryRadiologyBiology

Abstract

fetched live from OpenAlex

The clinical diagnosis of Alzheimer's disease (AD) is occasionally imprecise using consensus criteria for probable AD. Therefore, there is a great need for simple biomarkers that substantially aid early diagnosis and tract disease progression of AD and mild cognitive impairment. Of currently available biomarkers for AD, imaging markers are of particular importance based on their low invasiveness and reproducibility. In vivo detection of brain amyloid burden using positron emission tomography either by PIB or BF-227 would be quite attractive. In Japan, Alzheimer's disease neuroimaging initiatives (ADNI) has been launched in 2008 in accordance with US- and World-Wide ADNI. The paradigm of AD diagnosis and treatment would be shifted from "cognitive-based" to "biomarker-based" framework. The use of ideal biomarkers can remarkably speed up AD drug discovery by providing earliest signals of drug efficacy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.366
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueRinsho ShinkeigakuSame topicAlzheimer's disease research and treatmentsFrench-language works237,207